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<div class="title">HOGDescriptor.cpp</div>  </div>
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<a href="validation_2reference_2_h_o_g_descriptor_8cpp.xhtml">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno">    1</span>&#160;<span class="comment">/*</span></div><div class="line"><a name="l00002"></a><span class="lineno">    2</span>&#160;<span class="comment"> * Copyright (c) 2017-2018 ARM Limited.</span></div><div class="line"><a name="l00003"></a><span class="lineno">    3</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00004"></a><span class="lineno">    4</span>&#160;<span class="comment"> * SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00005"></a><span class="lineno">    5</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00006"></a><span class="lineno">    6</span>&#160;<span class="comment"> * Permission is hereby granted, free of charge, to any person obtaining a copy</span></div><div class="line"><a name="l00007"></a><span class="lineno">    7</span>&#160;<span class="comment"> * of this software and associated documentation files (the &quot;Software&quot;), to</span></div><div class="line"><a name="l00008"></a><span class="lineno">    8</span>&#160;<span class="comment"> * deal in the Software without restriction, including without limitation the</span></div><div class="line"><a name="l00009"></a><span class="lineno">    9</span>&#160;<span class="comment"> * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or</span></div><div class="line"><a name="l00010"></a><span class="lineno">   10</span>&#160;<span class="comment"> * sell copies of the Software, and to permit persons to whom the Software is</span></div><div class="line"><a name="l00011"></a><span class="lineno">   11</span>&#160;<span class="comment"> * furnished to do so, subject to the following conditions:</span></div><div class="line"><a name="l00012"></a><span class="lineno">   12</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00013"></a><span class="lineno">   13</span>&#160;<span class="comment"> * The above copyright notice and this permission notice shall be included in all</span></div><div class="line"><a name="l00014"></a><span class="lineno">   14</span>&#160;<span class="comment"> * copies or substantial portions of the Software.</span></div><div class="line"><a name="l00015"></a><span class="lineno">   15</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00016"></a><span class="lineno">   16</span>&#160;<span class="comment"> * THE SOFTWARE IS PROVIDED &quot;AS IS&quot;, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR</span></div><div class="line"><a name="l00017"></a><span class="lineno">   17</span>&#160;<span class="comment"> * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,</span></div><div class="line"><a name="l00018"></a><span class="lineno">   18</span>&#160;<span class="comment"> * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE</span></div><div class="line"><a name="l00019"></a><span class="lineno">   19</span>&#160;<span class="comment"> * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER</span></div><div class="line"><a name="l00020"></a><span class="lineno">   20</span>&#160;<span class="comment"> * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,</span></div><div class="line"><a name="l00021"></a><span class="lineno">   21</span>&#160;<span class="comment"> * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE</span></div><div class="line"><a name="l00022"></a><span class="lineno">   22</span>&#160;<span class="comment"> * SOFTWARE.</span></div><div class="line"><a name="l00023"></a><span class="lineno">   23</span>&#160;<span class="comment"> */</span></div><div class="line"><a name="l00024"></a><span class="lineno">   24</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_h_o_g_descriptor_8h.xhtml">HOGDescriptor.h</a>&quot;</span></div><div class="line"><a name="l00025"></a><span class="lineno">   25</span>&#160;</div><div class="line"><a name="l00026"></a><span class="lineno">   26</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_derivative_8h.xhtml">Derivative.h</a>&quot;</span></div><div class="line"><a name="l00027"></a><span class="lineno">   27</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_magnitude_8h.xhtml">Magnitude.h</a>&quot;</span></div><div class="line"><a name="l00028"></a><span class="lineno">   28</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_phase_8h.xhtml">Phase.h</a>&quot;</span></div><div class="line"><a name="l00029"></a><span class="lineno">   29</span>&#160;</div><div class="line"><a name="l00030"></a><span class="lineno">   30</span>&#160;<span class="keyword">namespace </span><a class="code" href="namespacearm__compute.xhtml">arm_compute</a></div><div class="line"><a name="l00031"></a><span class="lineno">   31</span>&#160;{</div><div class="line"><a name="l00032"></a><span class="lineno">   32</span>&#160;<span class="keyword">namespace </span>test</div><div class="line"><a name="l00033"></a><span class="lineno">   33</span>&#160;{</div><div class="line"><a name="l00034"></a><span class="lineno">   34</span>&#160;<span class="keyword">namespace </span>validation</div><div class="line"><a name="l00035"></a><span class="lineno">   35</span>&#160;{</div><div class="line"><a name="l00036"></a><span class="lineno">   36</span>&#160;<span class="keyword">namespace </span>reference</div><div class="line"><a name="l00037"></a><span class="lineno">   37</span>&#160;{</div><div class="line"><a name="l00038"></a><span class="lineno">   38</span>&#160;<span class="keyword">namespace</span></div><div class="line"><a name="l00039"></a><span class="lineno">   39</span>&#160;{</div><div class="line"><a name="l00040"></a><span class="lineno">   40</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T&gt;</div><div class="line"><a name="l00041"></a><span class="lineno">   41</span>&#160;<span class="keywordtype">void</span> hog_orientation_compute(<span class="keyword">const</span> SimpleTensor&lt;T&gt; &amp;mag, <span class="keyword">const</span> SimpleTensor&lt;T&gt; &amp;<a class="code" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#a74991bda4fcca3ce5dcf8afdccdbafff">phase</a>, std::vector&lt;T&gt; &amp;bins, <span class="keyword">const</span> HOGInfo &amp;hog_info)</div><div class="line"><a name="l00042"></a><span class="lineno">   42</span>&#160;{</div><div class="line"><a name="l00043"></a><span class="lineno">   43</span>&#160;    <span class="keyword">const</span> Size2D &amp;cell_size = hog_info.cell_size();</div><div class="line"><a name="l00044"></a><span class="lineno">   44</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">size_t</span>  num_bins  = hog_info.num_bins();</div><div class="line"><a name="l00045"></a><span class="lineno">   45</span>&#160;</div><div class="line"><a name="l00046"></a><span class="lineno">   46</span>&#160;    <span class="keywordtype">float</span> phase_scale = (<a class="code" href="namespacearm__compute.xhtml#af00a42ecad444bbda75cde1b64bd7e72a6898b46a1cde8a1572e2722c44c5ab07">PhaseType::SIGNED</a> == hog_info.phase_type() ? num_bins / 360.0f : num_bins / 180.0f);</div><div class="line"><a name="l00047"></a><span class="lineno">   47</span>&#160;    phase_scale *= (<a class="code" href="namespacearm__compute.xhtml#af00a42ecad444bbda75cde1b64bd7e72a6898b46a1cde8a1572e2722c44c5ab07">PhaseType::SIGNED</a> == hog_info.phase_type() ? 360.0f / 255.0f : 1.0f);</div><div class="line"><a name="l00048"></a><span class="lineno">   48</span>&#160;</div><div class="line"><a name="l00049"></a><span class="lineno">   49</span>&#160;    <span class="keywordtype">int</span> row_idx = 0;</div><div class="line"><a name="l00050"></a><span class="lineno">   50</span>&#160;    <span class="keywordflow">for</span>(<span class="keywordtype">size_t</span> yc = 0; yc &lt; cell_size.height; ++yc)</div><div class="line"><a name="l00051"></a><span class="lineno">   51</span>&#160;    {</div><div class="line"><a name="l00052"></a><span class="lineno">   52</span>&#160;        <span class="keywordflow">for</span>(<span class="keywordtype">size_t</span> xc = 0; xc &lt; cell_size.width; xc++)</div><div class="line"><a name="l00053"></a><span class="lineno">   53</span>&#160;        {</div><div class="line"><a name="l00054"></a><span class="lineno">   54</span>&#160;            <span class="keyword">const</span> <span class="keywordtype">float</span> mag_value   = mag[(row_idx + xc)];</div><div class="line"><a name="l00055"></a><span class="lineno">   55</span>&#160;            <span class="keyword">const</span> <span class="keywordtype">float</span> phase_value = phase[(row_idx + xc)] * phase_scale + 0.5f;</div><div class="line"><a name="l00056"></a><span class="lineno">   56</span>&#160;            <span class="keyword">const</span> <span class="keywordtype">float</span> w1          = phase_value - floor(phase_value);</div><div class="line"><a name="l00057"></a><span class="lineno">   57</span>&#160;</div><div class="line"><a name="l00058"></a><span class="lineno">   58</span>&#160;            <span class="comment">// The quantised phase is the histogram index [0, num_bins - 1]</span></div><div class="line"><a name="l00059"></a><span class="lineno">   59</span>&#160;            <span class="comment">// Check limit of histogram index. If hidx == num_bins, hidx = 0</span></div><div class="line"><a name="l00060"></a><span class="lineno">   60</span>&#160;            <span class="keyword">const</span> <span class="keyword">auto</span> hidx = <span class="keyword">static_cast&lt;</span><span class="keywordtype">unsigned</span> <span class="keywordtype">int</span><span class="keyword">&gt;</span>(phase_value) % num_bins;</div><div class="line"><a name="l00061"></a><span class="lineno">   61</span>&#160;</div><div class="line"><a name="l00062"></a><span class="lineno">   62</span>&#160;            <span class="comment">// Weighted vote between 2 bins</span></div><div class="line"><a name="l00063"></a><span class="lineno">   63</span>&#160;            bins[hidx] += mag_value * (1.0f - w1);</div><div class="line"><a name="l00064"></a><span class="lineno">   64</span>&#160;            bins[(hidx + 1) % num_bins] += mag_value * w1;</div><div class="line"><a name="l00065"></a><span class="lineno">   65</span>&#160;        }</div><div class="line"><a name="l00066"></a><span class="lineno">   66</span>&#160;</div><div class="line"><a name="l00067"></a><span class="lineno">   67</span>&#160;        row_idx += cell_size.width;</div><div class="line"><a name="l00068"></a><span class="lineno">   68</span>&#160;    }</div><div class="line"><a name="l00069"></a><span class="lineno">   69</span>&#160;}</div><div class="line"><a name="l00070"></a><span class="lineno">   70</span>&#160;</div><div class="line"><a name="l00071"></a><span class="lineno">   71</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T&gt;</div><div class="line"><a name="l00072"></a><span class="lineno">   72</span>&#160;<span class="keywordtype">void</span> hog_block_normalization_compute(SimpleTensor&lt;T&gt; &amp;block, SimpleTensor&lt;T&gt; &amp;desc, <span class="keyword">const</span> HOGInfo &amp;hog_info, <span class="keywordtype">size_t</span> block_idx)</div><div class="line"><a name="l00073"></a><span class="lineno">   73</span>&#160;{</div><div class="line"><a name="l00074"></a><span class="lineno">   74</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">int</span>         num_bins_per_block = desc.num_channels();</div><div class="line"><a name="l00075"></a><span class="lineno">   75</span>&#160;    <span class="keyword">const</span> <a class="code" href="namespacearm__compute.xhtml#a673665b4587a2956fcbad5f0e9ba89d3">HOGNormType</a> norm_type          = hog_info.normalization_type();</div><div class="line"><a name="l00076"></a><span class="lineno">   76</span>&#160;    <span class="keyword">const</span> Coordinates <span class="keywordtype">id</span>                 = <a class="code" href="namespacearm__compute_1_1test.xhtml#a24d8c0391cfa38e78969b6ad97c0ff09">index2coord</a>(desc.shape(), block_idx);</div><div class="line"><a name="l00077"></a><span class="lineno">   77</span>&#160;</div><div class="line"><a name="l00078"></a><span class="lineno">   78</span>&#160;    <span class="keywordtype">float</span> <a class="code" href="reduction__operation_8cl.xhtml#ab0df00f5333da51860deb93deb44a782">sum</a> = 0.0f;</div><div class="line"><a name="l00079"></a><span class="lineno">   79</span>&#160;</div><div class="line"><a name="l00080"></a><span class="lineno">   80</span>&#160;    <span class="comment">// Calculate sum</span></div><div class="line"><a name="l00081"></a><span class="lineno">   81</span>&#160;    <span class="keywordflow">for</span>(<span class="keywordtype">int</span> i = 0; i &lt; num_bins_per_block; ++i)</div><div class="line"><a name="l00082"></a><span class="lineno">   82</span>&#160;    {</div><div class="line"><a name="l00083"></a><span class="lineno">   83</span>&#160;        <span class="keyword">const</span> <span class="keywordtype">float</span> val = block[i];</div><div class="line"><a name="l00084"></a><span class="lineno">   84</span>&#160;        sum += (norm_type == <a class="code" href="namespacearm__compute.xhtml#a673665b4587a2956fcbad5f0e9ba89d3a68616ae21712c00705b962f4eff06eaa">HOGNormType::L1_NORM</a>) ? std::fabs(val) : val * val;</div><div class="line"><a name="l00085"></a><span class="lineno">   85</span>&#160;    }</div><div class="line"><a name="l00086"></a><span class="lineno">   86</span>&#160;</div><div class="line"><a name="l00087"></a><span class="lineno">   87</span>&#160;    <span class="comment">// Calculate normalization scale</span></div><div class="line"><a name="l00088"></a><span class="lineno">   88</span>&#160;    <span class="keywordtype">float</span> <a class="code" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#a83372886e5f41e1cd3631035d638c00b">scale</a> = 1.0f / (std::sqrt(sum) + num_bins_per_block * 0.1f);</div><div class="line"><a name="l00089"></a><span class="lineno">   89</span>&#160;</div><div class="line"><a name="l00090"></a><span class="lineno">   90</span>&#160;    <span class="keywordflow">if</span>(norm_type == <a class="code" href="namespacearm__compute.xhtml#a673665b4587a2956fcbad5f0e9ba89d3ac9e68c0594494ec85805b225a7acb9c2">HOGNormType::L2HYS_NORM</a>)</div><div class="line"><a name="l00091"></a><span class="lineno">   91</span>&#160;    {</div><div class="line"><a name="l00092"></a><span class="lineno">   92</span>&#160;        <span class="comment">// Reset sum</span></div><div class="line"><a name="l00093"></a><span class="lineno">   93</span>&#160;        sum = 0.0f;</div><div class="line"><a name="l00094"></a><span class="lineno">   94</span>&#160;        <span class="keywordflow">for</span>(<span class="keywordtype">int</span> i = 0; i &lt; num_bins_per_block; ++i)</div><div class="line"><a name="l00095"></a><span class="lineno">   95</span>&#160;        {</div><div class="line"><a name="l00096"></a><span class="lineno">   96</span>&#160;            <span class="keywordtype">float</span> val = block[i] * <a class="code" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#a83372886e5f41e1cd3631035d638c00b">scale</a>;</div><div class="line"><a name="l00097"></a><span class="lineno">   97</span>&#160;</div><div class="line"><a name="l00098"></a><span class="lineno">   98</span>&#160;            <span class="comment">// Clip scaled input_value if over l2_hyst_threshold</span></div><div class="line"><a name="l00099"></a><span class="lineno">   99</span>&#160;            val = fmin(val, hog_info.l2_hyst_threshold());</div><div class="line"><a name="l00100"></a><span class="lineno">  100</span>&#160;            sum += val * val;</div><div class="line"><a name="l00101"></a><span class="lineno">  101</span>&#160;            block[i] = val;</div><div class="line"><a name="l00102"></a><span class="lineno">  102</span>&#160;        }</div><div class="line"><a name="l00103"></a><span class="lineno">  103</span>&#160;</div><div class="line"><a name="l00104"></a><span class="lineno">  104</span>&#160;        <span class="comment">// We use the same constants of OpenCV</span></div><div class="line"><a name="l00105"></a><span class="lineno">  105</span>&#160;        scale = 1.0f / (std::sqrt(sum) + 1e-3f);</div><div class="line"><a name="l00106"></a><span class="lineno">  106</span>&#160;    }</div><div class="line"><a name="l00107"></a><span class="lineno">  107</span>&#160;</div><div class="line"><a name="l00108"></a><span class="lineno">  108</span>&#160;    <span class="keywordflow">for</span>(<span class="keywordtype">int</span> i = 0; i &lt; num_bins_per_block; ++i)</div><div class="line"><a name="l00109"></a><span class="lineno">  109</span>&#160;    {</div><div class="line"><a name="l00110"></a><span class="lineno">  110</span>&#160;        block[i] *= <a class="code" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#a83372886e5f41e1cd3631035d638c00b">scale</a>;</div><div class="line"><a name="l00111"></a><span class="lineno">  111</span>&#160;        <span class="keyword">reinterpret_cast&lt;</span><span class="keywordtype">float</span> *<span class="keyword">&gt;</span>(desc(<span class="keywordtype">id</span>))[i] = block[i];</div><div class="line"><a name="l00112"></a><span class="lineno">  112</span>&#160;    }</div><div class="line"><a name="l00113"></a><span class="lineno">  113</span>&#160;}</div><div class="line"><a name="l00114"></a><span class="lineno">  114</span>&#160;} <span class="comment">// namespace</span></div><div class="line"><a name="l00115"></a><span class="lineno">  115</span>&#160;</div><div class="line"><a name="l00116"></a><span class="lineno">  116</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T, <span class="keyword">typename</span> U, <span class="keyword">typename</span> V&gt;</div><div class="line"><a name="l00117"></a><span class="lineno"><a class="line" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#aed58e449c2d482b55d61ee6bfd0de984">  117</a></span>&#160;<span class="keywordtype">void</span> <a class="code" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#aed58e449c2d482b55d61ee6bfd0de984">hog_orientation_binning</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;T&gt;</a> &amp;mag, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;U&gt;</a> &amp;phase, <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;V&gt;</a> &amp;hog_space, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_h_o_g_info.xhtml">HOGInfo</a> &amp;hog_info)</div><div class="line"><a name="l00118"></a><span class="lineno">  118</span>&#160;{</div><div class="line"><a name="l00119"></a><span class="lineno">  119</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a> &amp;cell_size = hog_info.<a class="code" href="classarm__compute_1_1_h_o_g_info.xhtml#a4b7434680a85c2ac14df737ac7cca91e">cell_size</a>();</div><div class="line"><a name="l00120"></a><span class="lineno">  120</span>&#160;</div><div class="line"><a name="l00121"></a><span class="lineno">  121</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">size_t</span> num_bins     = hog_info.<a class="code" href="classarm__compute_1_1_h_o_g_info.xhtml#ae3664b841732a09d7749953ca5b81373">num_bins</a>();</div><div class="line"><a name="l00122"></a><span class="lineno">  122</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">size_t</span> shape_width  = hog_space.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aba5871b3e4a65d057ec1c28fce8b00ba">shape</a>().x() * hog_info.<a class="code" href="classarm__compute_1_1_h_o_g_info.xhtml#a4b7434680a85c2ac14df737ac7cca91e">cell_size</a>().<a class="code" href="classarm__compute_1_1_size2_d.xhtml#a02bed8590a9ddf520e58a060059518ec">width</a>;</div><div class="line"><a name="l00123"></a><span class="lineno">  123</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">size_t</span> shape_height = hog_space.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aba5871b3e4a65d057ec1c28fce8b00ba">shape</a>().y() * hog_info.<a class="code" href="classarm__compute_1_1_h_o_g_info.xhtml#a4b7434680a85c2ac14df737ac7cca91e">cell_size</a>().<a class="code" href="classarm__compute_1_1_size2_d.xhtml#a02afeaaf8574e7a78d6b466ff2695052">height</a>;</div><div class="line"><a name="l00124"></a><span class="lineno">  124</span>&#160;</div><div class="line"><a name="l00125"></a><span class="lineno">  125</span>&#160;    <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> cell_shape(cell_size.<a class="code" href="classarm__compute_1_1_size2_d.xhtml#a02bed8590a9ddf520e58a060059518ec">width</a>, cell_size.<a class="code" href="classarm__compute_1_1_size2_d.xhtml#a02afeaaf8574e7a78d6b466ff2695052">height</a>);</div><div class="line"><a name="l00126"></a><span class="lineno">  126</span>&#160;</div><div class="line"><a name="l00127"></a><span class="lineno">  127</span>&#160;    <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;V&gt;</a> mag_cell(cell_shape, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>);</div><div class="line"><a name="l00128"></a><span class="lineno">  128</span>&#160;    <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;V&gt;</a> phase_cell(cell_shape, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>);</div><div class="line"><a name="l00129"></a><span class="lineno">  129</span>&#160;</div><div class="line"><a name="l00130"></a><span class="lineno">  130</span>&#160;    <span class="keywordtype">int</span> cell_idx = 0;</div><div class="line"><a name="l00131"></a><span class="lineno">  131</span>&#160;    <span class="keywordtype">int</span> y_offset = 0;</div><div class="line"><a name="l00132"></a><span class="lineno">  132</span>&#160;</div><div class="line"><a name="l00133"></a><span class="lineno">  133</span>&#160;    <span class="comment">// Traverse shape</span></div><div class="line"><a name="l00134"></a><span class="lineno">  134</span>&#160;    <span class="keywordflow">for</span>(<span class="keyword">auto</span> sy = cell_size.<a class="code" href="classarm__compute_1_1_size2_d.xhtml#a02afeaaf8574e7a78d6b466ff2695052">height</a>; sy &lt;= shape_height; sy += cell_size.<a class="code" href="classarm__compute_1_1_size2_d.xhtml#a02afeaaf8574e7a78d6b466ff2695052">height</a>)</div><div class="line"><a name="l00135"></a><span class="lineno">  135</span>&#160;    {</div><div class="line"><a name="l00136"></a><span class="lineno">  136</span>&#160;        <span class="keywordtype">int</span> x_offset = 0;</div><div class="line"><a name="l00137"></a><span class="lineno">  137</span>&#160;        <span class="keywordflow">for</span>(<span class="keyword">auto</span> sx = cell_size.<a class="code" href="classarm__compute_1_1_size2_d.xhtml#a02bed8590a9ddf520e58a060059518ec">width</a>; sx &lt;= shape_width; sx += cell_size.<a class="code" href="classarm__compute_1_1_size2_d.xhtml#a02bed8590a9ddf520e58a060059518ec">width</a>)</div><div class="line"><a name="l00138"></a><span class="lineno">  138</span>&#160;        {</div><div class="line"><a name="l00139"></a><span class="lineno">  139</span>&#160;            <span class="keywordtype">int</span> row_idx  = 0;</div><div class="line"><a name="l00140"></a><span class="lineno">  140</span>&#160;            <span class="keywordtype">int</span> elem_idx = 0;</div><div class="line"><a name="l00141"></a><span class="lineno">  141</span>&#160;</div><div class="line"><a name="l00142"></a><span class="lineno">  142</span>&#160;            <span class="comment">// Traverse cell</span></div><div class="line"><a name="l00143"></a><span class="lineno">  143</span>&#160;            <span class="keywordflow">for</span>(<span class="keyword">auto</span> y = 0u; y &lt; cell_size.<a class="code" href="classarm__compute_1_1_size2_d.xhtml#a02afeaaf8574e7a78d6b466ff2695052">height</a>; ++y)</div><div class="line"><a name="l00144"></a><span class="lineno">  144</span>&#160;            {</div><div class="line"><a name="l00145"></a><span class="lineno">  145</span>&#160;                <span class="keywordflow">for</span>(<span class="keyword">auto</span> x = 0u; x &lt; cell_size.<a class="code" href="classarm__compute_1_1_size2_d.xhtml#a02bed8590a9ddf520e58a060059518ec">width</a>; ++x)</div><div class="line"><a name="l00146"></a><span class="lineno">  146</span>&#160;                {</div><div class="line"><a name="l00147"></a><span class="lineno">  147</span>&#160;                    <span class="keywordtype">int</span> shape_idx        = x + row_idx + x_offset + y_offset;</div><div class="line"><a name="l00148"></a><span class="lineno">  148</span>&#160;                    mag_cell[elem_idx]   = mag[shape_idx];</div><div class="line"><a name="l00149"></a><span class="lineno">  149</span>&#160;                    phase_cell[elem_idx] = phase[shape_idx];</div><div class="line"><a name="l00150"></a><span class="lineno">  150</span>&#160;                    elem_idx++;</div><div class="line"><a name="l00151"></a><span class="lineno">  151</span>&#160;                }</div><div class="line"><a name="l00152"></a><span class="lineno">  152</span>&#160;</div><div class="line"><a name="l00153"></a><span class="lineno">  153</span>&#160;                row_idx += shape_width;</div><div class="line"><a name="l00154"></a><span class="lineno">  154</span>&#160;            }</div><div class="line"><a name="l00155"></a><span class="lineno">  155</span>&#160;</div><div class="line"><a name="l00156"></a><span class="lineno">  156</span>&#160;            <span class="comment">// Partition magnitude values into bins based on phase values</span></div><div class="line"><a name="l00157"></a><span class="lineno">  157</span>&#160;            std::vector&lt;V&gt; bins(num_bins);</div><div class="line"><a name="l00158"></a><span class="lineno">  158</span>&#160;            hog_orientation_compute(mag_cell, phase_cell, bins, hog_info);</div><div class="line"><a name="l00159"></a><span class="lineno">  159</span>&#160;</div><div class="line"><a name="l00160"></a><span class="lineno">  160</span>&#160;            <span class="keywordflow">for</span>(<span class="keywordtype">size_t</span> i = 0; i &lt; num_bins; ++i)</div><div class="line"><a name="l00161"></a><span class="lineno">  161</span>&#160;            {</div><div class="line"><a name="l00162"></a><span class="lineno">  162</span>&#160;                hog_space[cell_idx * num_bins + i] = bins[i];</div><div class="line"><a name="l00163"></a><span class="lineno">  163</span>&#160;            }</div><div class="line"><a name="l00164"></a><span class="lineno">  164</span>&#160;</div><div class="line"><a name="l00165"></a><span class="lineno">  165</span>&#160;            x_offset += cell_size.<a class="code" href="classarm__compute_1_1_size2_d.xhtml#a02bed8590a9ddf520e58a060059518ec">width</a>;</div><div class="line"><a name="l00166"></a><span class="lineno">  166</span>&#160;            cell_idx++;</div><div class="line"><a name="l00167"></a><span class="lineno">  167</span>&#160;        }</div><div class="line"><a name="l00168"></a><span class="lineno">  168</span>&#160;</div><div class="line"><a name="l00169"></a><span class="lineno">  169</span>&#160;        y_offset += (cell_size.<a class="code" href="classarm__compute_1_1_size2_d.xhtml#a02afeaaf8574e7a78d6b466ff2695052">height</a> * shape_width);</div><div class="line"><a name="l00170"></a><span class="lineno">  170</span>&#160;    }</div><div class="line"><a name="l00171"></a><span class="lineno">  171</span>&#160;}</div><div class="line"><a name="l00172"></a><span class="lineno">  172</span>&#160;</div><div class="line"><a name="l00173"></a><span class="lineno">  173</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T&gt;</div><div class="line"><a name="l00174"></a><span class="lineno"><a class="line" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#ae01f1c200a32d41a056d513760981326">  174</a></span>&#160;<span class="keywordtype">void</span> <a class="code" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#ae01f1c200a32d41a056d513760981326">hog_block_normalization</a>(<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;T&gt;</a> &amp;desc, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;T&gt;</a> &amp;hog_space, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_h_o_g_info.xhtml">HOGInfo</a> &amp;hog_info)</div><div class="line"><a name="l00175"></a><span class="lineno">  175</span>&#160;{</div><div class="line"><a name="l00176"></a><span class="lineno">  176</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a>  cells_per_block        = hog_info.<a class="code" href="classarm__compute_1_1_h_o_g_info.xhtml#adb20b5249eedf180a461ea097622fe7f">num_cells_per_block</a>();</div><div class="line"><a name="l00177"></a><span class="lineno">  177</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a>  cells_per_block_stride = hog_info.<a class="code" href="classarm__compute_1_1_h_o_g_info.xhtml#a932db6ec1490ede3ff23e8c0ce80865c">num_cells_per_block_stride</a>();</div><div class="line"><a name="l00178"></a><span class="lineno">  178</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a> &amp;block_size             = hog_info.<a class="code" href="classarm__compute_1_1_h_o_g_info.xhtml#a13a9a6f5cfa21b3ab15b1e4315311aeb">block_size</a>();</div><div class="line"><a name="l00179"></a><span class="lineno">  179</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a> &amp;block_stride           = hog_info.<a class="code" href="classarm__compute_1_1_h_o_g_info.xhtml#aa9a69eade27460f843fcfba5abb7ae52">block_stride</a>();</div><div class="line"><a name="l00180"></a><span class="lineno">  180</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">size_t</span>  num_bins               = hog_info.<a class="code" href="classarm__compute_1_1_h_o_g_info.xhtml#ae3664b841732a09d7749953ca5b81373">num_bins</a>();</div><div class="line"><a name="l00181"></a><span class="lineno">  181</span>&#160;</div><div class="line"><a name="l00182"></a><span class="lineno">  182</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">size_t</span> shape_width          = hog_space.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aba5871b3e4a65d057ec1c28fce8b00ba">shape</a>().x() * hog_info.<a class="code" href="classarm__compute_1_1_h_o_g_info.xhtml#a4b7434680a85c2ac14df737ac7cca91e">cell_size</a>().<a class="code" href="classarm__compute_1_1_size2_d.xhtml#a02bed8590a9ddf520e58a060059518ec">width</a>;</div><div class="line"><a name="l00183"></a><span class="lineno">  183</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">size_t</span> shape_height         = hog_space.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aba5871b3e4a65d057ec1c28fce8b00ba">shape</a>().y() * hog_info.<a class="code" href="classarm__compute_1_1_h_o_g_info.xhtml#a4b7434680a85c2ac14df737ac7cca91e">cell_size</a>().<a class="code" href="classarm__compute_1_1_size2_d.xhtml#a02afeaaf8574e7a78d6b466ff2695052">height</a>;</div><div class="line"><a name="l00184"></a><span class="lineno">  184</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">size_t</span> num_bins_per_block_x = cells_per_block.<a class="code" href="classarm__compute_1_1_size2_d.xhtml#a02bed8590a9ddf520e58a060059518ec">width</a> * num_bins;</div><div class="line"><a name="l00185"></a><span class="lineno">  185</span>&#160;</div><div class="line"><a name="l00186"></a><span class="lineno">  186</span>&#160;    <span class="comment">// Tensor representing single block</span></div><div class="line"><a name="l00187"></a><span class="lineno">  187</span>&#160;    <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;T&gt;</a> block(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>{ 1u, 1u }, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>, cells_per_block.<a class="code" href="classarm__compute_1_1_size2_d.xhtml#ab220a7dd0ff5c86b4ba8acdf75af3252">area</a>() * num_bins);</div><div class="line"><a name="l00188"></a><span class="lineno">  188</span>&#160;</div><div class="line"><a name="l00189"></a><span class="lineno">  189</span>&#160;    <span class="keywordtype">int</span> block_idx      = 0;</div><div class="line"><a name="l00190"></a><span class="lineno">  190</span>&#160;    <span class="keywordtype">int</span> block_y_offset = 0;</div><div class="line"><a name="l00191"></a><span class="lineno">  191</span>&#160;</div><div class="line"><a name="l00192"></a><span class="lineno">  192</span>&#160;    <span class="comment">// Traverse shape</span></div><div class="line"><a name="l00193"></a><span class="lineno">  193</span>&#160;    <span class="keywordflow">for</span>(<span class="keyword">auto</span> sy = block_size.<a class="code" href="classarm__compute_1_1_size2_d.xhtml#a02afeaaf8574e7a78d6b466ff2695052">height</a>; sy &lt;= shape_height; sy += block_stride.<a class="code" href="classarm__compute_1_1_size2_d.xhtml#a02afeaaf8574e7a78d6b466ff2695052">height</a>)</div><div class="line"><a name="l00194"></a><span class="lineno">  194</span>&#160;    {</div><div class="line"><a name="l00195"></a><span class="lineno">  195</span>&#160;        <span class="keywordtype">int</span> block_x_offset = 0;</div><div class="line"><a name="l00196"></a><span class="lineno">  196</span>&#160;        <span class="keywordflow">for</span>(<span class="keyword">auto</span> sx = block_size.<a class="code" href="classarm__compute_1_1_size2_d.xhtml#a02bed8590a9ddf520e58a060059518ec">width</a>; sx &lt;= shape_width; sx += block_stride.<a class="code" href="classarm__compute_1_1_size2_d.xhtml#a02bed8590a9ddf520e58a060059518ec">width</a>)</div><div class="line"><a name="l00197"></a><span class="lineno">  197</span>&#160;        {</div><div class="line"><a name="l00198"></a><span class="lineno">  198</span>&#160;            <span class="keywordtype">int</span> cell_y_offset = 0;</div><div class="line"><a name="l00199"></a><span class="lineno">  199</span>&#160;            <span class="keywordtype">int</span> elem_idx      = 0;</div><div class="line"><a name="l00200"></a><span class="lineno">  200</span>&#160;</div><div class="line"><a name="l00201"></a><span class="lineno">  201</span>&#160;            <span class="comment">// Traverse block</span></div><div class="line"><a name="l00202"></a><span class="lineno">  202</span>&#160;            <span class="keywordflow">for</span>(<span class="keyword">auto</span> y = 0u; y &lt; cells_per_block.<a class="code" href="classarm__compute_1_1_size2_d.xhtml#a02afeaaf8574e7a78d6b466ff2695052">height</a>; ++y)</div><div class="line"><a name="l00203"></a><span class="lineno">  203</span>&#160;            {</div><div class="line"><a name="l00204"></a><span class="lineno">  204</span>&#160;                <span class="keywordflow">for</span>(<span class="keyword">auto</span> x = 0u; x &lt; num_bins_per_block_x; ++x)</div><div class="line"><a name="l00205"></a><span class="lineno">  205</span>&#160;                {</div><div class="line"><a name="l00206"></a><span class="lineno">  206</span>&#160;                    <span class="keywordtype">int</span> idx         = x + cell_y_offset + block_x_offset + block_y_offset;</div><div class="line"><a name="l00207"></a><span class="lineno">  207</span>&#160;                    block[elem_idx] = hog_space[idx];</div><div class="line"><a name="l00208"></a><span class="lineno">  208</span>&#160;                    elem_idx++;</div><div class="line"><a name="l00209"></a><span class="lineno">  209</span>&#160;                }</div><div class="line"><a name="l00210"></a><span class="lineno">  210</span>&#160;</div><div class="line"><a name="l00211"></a><span class="lineno">  211</span>&#160;                cell_y_offset += hog_space.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aba5871b3e4a65d057ec1c28fce8b00ba">shape</a>().x() * num_bins;</div><div class="line"><a name="l00212"></a><span class="lineno">  212</span>&#160;            }</div><div class="line"><a name="l00213"></a><span class="lineno">  213</span>&#160;</div><div class="line"><a name="l00214"></a><span class="lineno">  214</span>&#160;            <span class="comment">// Normalize block and write to descriptor</span></div><div class="line"><a name="l00215"></a><span class="lineno">  215</span>&#160;            hog_block_normalization_compute(block, desc, hog_info, block_idx);</div><div class="line"><a name="l00216"></a><span class="lineno">  216</span>&#160;</div><div class="line"><a name="l00217"></a><span class="lineno">  217</span>&#160;            block_x_offset += cells_per_block_stride.<a class="code" href="classarm__compute_1_1_size2_d.xhtml#a02bed8590a9ddf520e58a060059518ec">width</a> * num_bins;</div><div class="line"><a name="l00218"></a><span class="lineno">  218</span>&#160;            block_idx++;</div><div class="line"><a name="l00219"></a><span class="lineno">  219</span>&#160;        }</div><div class="line"><a name="l00220"></a><span class="lineno">  220</span>&#160;</div><div class="line"><a name="l00221"></a><span class="lineno">  221</span>&#160;        block_y_offset += cells_per_block_stride.<a class="code" href="classarm__compute_1_1_size2_d.xhtml#a02afeaaf8574e7a78d6b466ff2695052">height</a> * num_bins * hog_space.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aba5871b3e4a65d057ec1c28fce8b00ba">shape</a>().x();</div><div class="line"><a name="l00222"></a><span class="lineno">  222</span>&#160;    }</div><div class="line"><a name="l00223"></a><span class="lineno">  223</span>&#160;}</div><div class="line"><a name="l00224"></a><span class="lineno">  224</span>&#160;</div><div class="line"><a name="l00225"></a><span class="lineno">  225</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T, <span class="keyword">typename</span> U&gt;</div><div class="line"><a name="l00226"></a><span class="lineno"><a class="line" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#aa0803d3eb7f6177d7ff8eb49cf0772ab">  226</a></span>&#160;<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;T&gt;</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#aa0803d3eb7f6177d7ff8eb49cf0772ab">hog_descriptor</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;U&gt;</a> &amp;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a6743f0a130e8311e6f5b1a23df102472">src</a>, <a class="code" href="namespacearm__compute.xhtml#a15a05537a472ee742404821851529327">BorderMode</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5471e46933e7a9c4709972d91fc4ea65">border_mode</a>, U constant_border_value, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_h_o_g_info.xhtml">HOGInfo</a> &amp;hog_info)</div><div class="line"><a name="l00227"></a><span class="lineno">  227</span>&#160;{</div><div class="line"><a name="l00228"></a><span class="lineno">  228</span>&#160;    <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;int16_t&gt;</a> grad_x;</div><div class="line"><a name="l00229"></a><span class="lineno">  229</span>&#160;    <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;int16_t&gt;</a> grad_y;</div><div class="line"><a name="l00230"></a><span class="lineno">  230</span>&#160;</div><div class="line"><a name="l00231"></a><span class="lineno">  231</span>&#160;    <span class="comment">// Create tensor info for HOG descriptor</span></div><div class="line"><a name="l00232"></a><span class="lineno">  232</span>&#160;    <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>      desc_info(hog_info, src.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aba5871b3e4a65d057ec1c28fce8b00ba">shape</a>().x(), src.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aba5871b3e4a65d057ec1c28fce8b00ba">shape</a>().y());</div><div class="line"><a name="l00233"></a><span class="lineno">  233</span>&#160;    <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;T&gt;</a> desc(desc_info.tensor_shape(), <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>, desc_info.num_channels());</div><div class="line"><a name="l00234"></a><span class="lineno">  234</span>&#160;</div><div class="line"><a name="l00235"></a><span class="lineno">  235</span>&#160;    <span class="comment">// Create HOG space tensor (num_cells_x, num_cells_y)</span></div><div class="line"><a name="l00236"></a><span class="lineno">  236</span>&#160;    <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> hog_space_shape(src.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aba5871b3e4a65d057ec1c28fce8b00ba">shape</a>().x() / hog_info.<a class="code" href="classarm__compute_1_1_h_o_g_info.xhtml#a4b7434680a85c2ac14df737ac7cca91e">cell_size</a>().<a class="code" href="classarm__compute_1_1_size2_d.xhtml#a02bed8590a9ddf520e58a060059518ec">width</a>,</div><div class="line"><a name="l00237"></a><span class="lineno">  237</span>&#160;                                src.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aba5871b3e4a65d057ec1c28fce8b00ba">shape</a>().y() / hog_info.<a class="code" href="classarm__compute_1_1_h_o_g_info.xhtml#a4b7434680a85c2ac14df737ac7cca91e">cell_size</a>().<a class="code" href="classarm__compute_1_1_size2_d.xhtml#a02afeaaf8574e7a78d6b466ff2695052">height</a>);</div><div class="line"><a name="l00238"></a><span class="lineno">  238</span>&#160;</div><div class="line"><a name="l00239"></a><span class="lineno">  239</span>&#160;    <span class="comment">// For each cell a histogram with a num_bins is created</span></div><div class="line"><a name="l00240"></a><span class="lineno">  240</span>&#160;    <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>      info_hog_space(hog_space_shape, hog_info.<a class="code" href="classarm__compute_1_1_h_o_g_info.xhtml#ae3664b841732a09d7749953ca5b81373">num_bins</a>(), <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>);</div><div class="line"><a name="l00241"></a><span class="lineno">  241</span>&#160;    <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;T&gt;</a> hog_space(info_hog_space.tensor_shape(), <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>, info_hog_space.num_channels());</div><div class="line"><a name="l00242"></a><span class="lineno">  242</span>&#160;</div><div class="line"><a name="l00243"></a><span class="lineno">  243</span>&#160;    <span class="comment">// Calculate derivative</span></div><div class="line"><a name="l00244"></a><span class="lineno">  244</span>&#160;    std::tie(grad_x, grad_y) = derivative&lt;int16_t&gt;(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a6743f0a130e8311e6f5b1a23df102472">src</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5471e46933e7a9c4709972d91fc4ea65">border_mode</a>, constant_border_value, <a class="code" href="namespacearm__compute.xhtml#ae46abc5ecac309cbece5c06cb80daaf7a5515a637eda61b978e97adaa5d7629cc">GradientDimension::GRAD_XY</a>);</div><div class="line"><a name="l00245"></a><span class="lineno">  245</span>&#160;</div><div class="line"><a name="l00246"></a><span class="lineno">  246</span>&#160;    <span class="comment">// For each cell create histogram based on magnitude and phase</span></div><div class="line"><a name="l00247"></a><span class="lineno">  247</span>&#160;    <a class="code" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#aed58e449c2d482b55d61ee6bfd0de984">hog_orientation_binning</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#a6aa278cb3dd1777e7338c5e573c55550">magnitude</a>(grad_x, grad_y, <a class="code" href="namespacearm__compute.xhtml#a7b3ec6413f000b02fdb4e39a951d9f8aad927ac799e8b24f80fc80d89b2eb7131">MagnitudeType::L2NORM</a>),</div><div class="line"><a name="l00248"></a><span class="lineno">  248</span>&#160;                            <a class="code" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#a74991bda4fcca3ce5dcf8afdccdbafff">phase</a>(grad_x, grad_y, hog_info.<a class="code" href="classarm__compute_1_1_h_o_g_info.xhtml#a96823b4d7dc642aa9f51a0077899d3f9">phase_type</a>()),</div><div class="line"><a name="l00249"></a><span class="lineno">  249</span>&#160;                            hog_space,</div><div class="line"><a name="l00250"></a><span class="lineno">  250</span>&#160;                            hog_info);</div><div class="line"><a name="l00251"></a><span class="lineno">  251</span>&#160;</div><div class="line"><a name="l00252"></a><span class="lineno">  252</span>&#160;    <span class="comment">// Normalize histograms based on block size</span></div><div class="line"><a name="l00253"></a><span class="lineno">  253</span>&#160;    <a class="code" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#ae01f1c200a32d41a056d513760981326">hog_block_normalization</a>(desc, hog_space, hog_info);</div><div class="line"><a name="l00254"></a><span class="lineno">  254</span>&#160;</div><div class="line"><a name="l00255"></a><span class="lineno">  255</span>&#160;    <span class="keywordflow">return</span> desc;</div><div class="line"><a name="l00256"></a><span class="lineno">  256</span>&#160;}</div><div class="line"><a name="l00257"></a><span class="lineno">  257</span>&#160;</div><div class="line"><a name="l00258"></a><span class="lineno">  258</span>&#160;<span class="keyword">template</span> <span class="keywordtype">void</span> <a class="code" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#aed58e449c2d482b55d61ee6bfd0de984">hog_orientation_binning</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;int16_t&gt;</a> &amp;mag, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;uint8_t&gt;</a> &amp;phase, <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;float&gt;</a> &amp;hog_space, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_h_o_g_info.xhtml">HOGInfo</a> &amp;hog_info);</div><div class="line"><a name="l00259"></a><span class="lineno">  259</span>&#160;<span class="keyword">template</span> <span class="keywordtype">void</span> <a class="code" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#ae01f1c200a32d41a056d513760981326">hog_block_normalization</a>(<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;float&gt;</a> &amp;desc, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;float&gt;</a> &amp;hog_space, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_h_o_g_info.xhtml">HOGInfo</a> &amp;hog_info);</div><div class="line"><a name="l00260"></a><span class="lineno">  260</span>&#160;<span class="keyword">template</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;float&gt;</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#aa0803d3eb7f6177d7ff8eb49cf0772ab">hog_descriptor</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;uint8_t&gt;</a> &amp;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a6743f0a130e8311e6f5b1a23df102472">src</a>, <a class="code" href="namespacearm__compute.xhtml#a15a05537a472ee742404821851529327">BorderMode</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5471e46933e7a9c4709972d91fc4ea65">border_mode</a>, uint8_t constant_border_value, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_h_o_g_info.xhtml">HOGInfo</a> &amp;hog_info);</div><div class="line"><a name="l00261"></a><span class="lineno">  261</span>&#160;} <span class="comment">// namespace reference</span></div><div class="line"><a name="l00262"></a><span class="lineno">  262</span>&#160;} <span class="comment">// namespace validation</span></div><div class="line"><a name="l00263"></a><span class="lineno">  263</span>&#160;} <span class="comment">// namespace test</span></div><div class="line"><a name="l00264"></a><span class="lineno">  264</span>&#160;} <span class="comment">// namespace arm_compute</span></div><div class="ttc" id="namespacearm__compute_xhtml_a15a05537a472ee742404821851529327"><div class="ttname"><a href="namespacearm__compute.xhtml#a15a05537a472ee742404821851529327">arm_compute::BorderMode</a></div><div class="ttdeci">BorderMode</div><div class="ttdoc">Methods available to handle borders. </div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00283">Types.h:283</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_a673665b4587a2956fcbad5f0e9ba89d3ac9e68c0594494ec85805b225a7acb9c2"><div class="ttname"><a href="namespacearm__compute.xhtml#a673665b4587a2956fcbad5f0e9ba89d3ac9e68c0594494ec85805b225a7acb9c2">arm_compute::HOGNormType::L2HYS_NORM</a></div><div class="ttdoc">L2-norm followed by clipping. </div></div>
<div class="ttc" id="classarm__compute_1_1_h_o_g_info_xhtml_a96823b4d7dc642aa9f51a0077899d3f9"><div class="ttname"><a href="classarm__compute_1_1_h_o_g_info.xhtml#a96823b4d7dc642aa9f51a0077899d3f9">arm_compute::HOGInfo::phase_type</a></div><div class="ttdeci">PhaseType phase_type() const </div><div class="ttdoc">The type of PhaseType. </div></div>
<div class="ttc" id="classarm__compute_1_1_tensor_shape_xhtml"><div class="ttname"><a href="classarm__compute_1_1_tensor_shape.xhtml">arm_compute::TensorShape</a></div><div class="ttdoc">Shape of a tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_shape_8h_source.xhtml#l00039">TensorShape.h:39</a></div></div>
<div class="ttc" id="classarm__compute_1_1_h_o_g_info_xhtml_a932db6ec1490ede3ff23e8c0ce80865c"><div class="ttname"><a href="classarm__compute_1_1_h_o_g_info.xhtml#a932db6ec1490ede3ff23e8c0ce80865c">arm_compute::HOGInfo::num_cells_per_block_stride</a></div><div class="ttdeci">Size2D num_cells_per_block_stride() const </div><div class="ttdoc">Calculates the number of cells per block stride. </div></div>
<div class="ttc" id="namespacearm__compute_xhtml_af00a42ecad444bbda75cde1b64bd7e72a6898b46a1cde8a1572e2722c44c5ab07"><div class="ttname"><a href="namespacearm__compute.xhtml#af00a42ecad444bbda75cde1b64bd7e72a6898b46a1cde8a1572e2722c44c5ab07">arm_compute::PhaseType::SIGNED</a></div><div class="ttdoc">Angle range: [0, 360]. </div></div>
<div class="ttc" id="classarm__compute_1_1_h_o_g_info_xhtml_adb20b5249eedf180a461ea097622fe7f"><div class="ttname"><a href="classarm__compute_1_1_h_o_g_info.xhtml#adb20b5249eedf180a461ea097622fe7f">arm_compute::HOGInfo::num_cells_per_block</a></div><div class="ttdeci">Size2D num_cells_per_block() const </div><div class="ttdoc">Calculates the number of cells for each block. </div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_1_1reference_xhtml_aed58e449c2d482b55d61ee6bfd0de984"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#aed58e449c2d482b55d61ee6bfd0de984">arm_compute::test::validation::reference::hog_orientation_binning</a></div><div class="ttdeci">void hog_orientation_binning(const SimpleTensor&lt; T &gt; &amp;mag, const SimpleTensor&lt; U &gt; &amp;phase, SimpleTensor&lt; V &gt; &amp;hog_space, const HOGInfo &amp;hog_info)</div><div class="ttdef"><b>Definition:</b> <a href="validation_2reference_2_h_o_g_descriptor_8cpp_source.xhtml#l00117">HOGDescriptor.cpp:117</a></div></div>
<div class="ttc" id="reduction__operation_8cl_xhtml_ab0df00f5333da51860deb93deb44a782"><div class="ttname"><a href="reduction__operation_8cl.xhtml#ab0df00f5333da51860deb93deb44a782">sum</a></div><div class="ttdeci">DATA_TYPE sum(__global const DATA_TYPE *input)</div><div class="ttdoc">Calculate sum of a vector. </div><div class="ttdef"><b>Definition:</b> <a href="reduction__operation_8cl_source.xhtml#l00052">reduction_operation.cl:52</a></div></div>
<div class="ttc" id="classarm__compute_1_1_h_o_g_info_xhtml"><div class="ttname"><a href="classarm__compute_1_1_h_o_g_info.xhtml">arm_compute::HOGInfo</a></div><div class="ttdoc">Store the HOG&amp;#39;s metadata. </div><div class="ttdef"><b>Definition:</b> <a href="_h_o_g_info_8h_source.xhtml#l00035">HOGInfo.h:35</a></div></div>
<div class="ttc" id="classarm__compute_1_1_h_o_g_info_xhtml_a4b7434680a85c2ac14df737ac7cca91e"><div class="ttname"><a href="classarm__compute_1_1_h_o_g_info.xhtml#a4b7434680a85c2ac14df737ac7cca91e">arm_compute::HOGInfo::cell_size</a></div><div class="ttdeci">const Size2D &amp; cell_size() const </div><div class="ttdoc">The cell size in pixels. </div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">arm_compute::Format::F32</a></div><div class="ttdoc">1 channel, 1 F32 per channel </div></div>
<div class="ttc" id="_phase_8h_xhtml"><div class="ttname"><a href="_phase_8h.xhtml">Phase.h</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_1_1reference_xhtml_a74991bda4fcca3ce5dcf8afdccdbafff"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#a74991bda4fcca3ce5dcf8afdccdbafff">arm_compute::test::validation::reference::phase</a></div><div class="ttdeci">SimpleTensor&lt; uint8_t &gt; phase(const SimpleTensor&lt; T &gt; &amp;gx, const SimpleTensor&lt; T &gt; &amp;gy, PhaseType phase_type)</div><div class="ttdef"><b>Definition:</b> <a href="validation_2reference_2_phase_8cpp_source.xhtml#l00035">Phase.cpp:35</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml_aba5871b3e4a65d057ec1c28fce8b00ba"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aba5871b3e4a65d057ec1c28fce8b00ba">arm_compute::test::SimpleTensor::shape</a></div><div class="ttdeci">TensorShape shape() const override</div><div class="ttdoc">Shape of the tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00294">SimpleTensor.h:294</a></div></div>
<div class="ttc" id="classarm__compute_1_1_h_o_g_info_xhtml_aa9a69eade27460f843fcfba5abb7ae52"><div class="ttname"><a href="classarm__compute_1_1_h_o_g_info.xhtml#aa9a69eade27460f843fcfba5abb7ae52">arm_compute::HOGInfo::block_stride</a></div><div class="ttdeci">const Size2D &amp; block_stride() const </div><div class="ttdoc">The block stride in pixels. </div></div>
<div class="ttc" id="namespacearm__compute_xhtml"><div class="ttname"><a href="namespacearm__compute.xhtml">arm_compute</a></div><div class="ttdoc">This file contains all available output stages for GEMMLowp on OpenCL. </div><div class="ttdef"><b>Definition:</b> <a href="00__introduction_8dox_source.xhtml#l00001">00_introduction.dox:1</a></div></div>
<div class="ttc" id="classarm__compute_1_1_size2_d_xhtml_a02afeaaf8574e7a78d6b466ff2695052"><div class="ttname"><a href="classarm__compute_1_1_size2_d.xhtml#a02afeaaf8574e7a78d6b466ff2695052">arm_compute::Size2D::height</a></div><div class="ttdeci">size_t height</div><div class="ttdoc">Height of the image region or rectangle. </div><div class="ttdef"><b>Definition:</b> <a href="_size2_d_8h_source.xhtml#l00093">Size2D.h:93</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_1_1reference_xhtml_aa0803d3eb7f6177d7ff8eb49cf0772ab"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#aa0803d3eb7f6177d7ff8eb49cf0772ab">arm_compute::test::validation::reference::hog_descriptor</a></div><div class="ttdeci">SimpleTensor&lt; T &gt; hog_descriptor(const SimpleTensor&lt; U &gt; &amp;src, BorderMode border_mode, U constant_border_value, const HOGInfo &amp;hog_info)</div><div class="ttdef"><b>Definition:</b> <a href="validation_2reference_2_h_o_g_descriptor_8cpp_source.xhtml#l00226">HOGDescriptor.cpp:226</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_a673665b4587a2956fcbad5f0e9ba89d3a68616ae21712c00705b962f4eff06eaa"><div class="ttname"><a href="namespacearm__compute.xhtml#a673665b4587a2956fcbad5f0e9ba89d3a68616ae21712c00705b962f4eff06eaa">arm_compute::HOGNormType::L1_NORM</a></div><div class="ttdoc">L1 norm. </div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a5471e46933e7a9c4709972d91fc4ea65"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a5471e46933e7a9c4709972d91fc4ea65">arm_compute::test::validation::border_mode</a></div><div class="ttdeci">border_mode</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_convolution_8cpp_source.xhtml#l00133">Convolution.cpp:133</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_xhtml_a24d8c0391cfa38e78969b6ad97c0ff09"><div class="ttname"><a href="namespacearm__compute_1_1test.xhtml#a24d8c0391cfa38e78969b6ad97c0ff09">arm_compute::test::index2coord</a></div><div class="ttdeci">Coordinates index2coord(const TensorShape &amp;shape, int index)</div><div class="ttdoc">Convert a linear index into n-dimensional coordinates. </div><div class="ttdef"><b>Definition:</b> <a href="tests_2_utils_8h_source.xhtml#l00419">Utils.h:419</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_a7b3ec6413f000b02fdb4e39a951d9f8aad927ac799e8b24f80fc80d89b2eb7131"><div class="ttname"><a href="namespacearm__compute.xhtml#a7b3ec6413f000b02fdb4e39a951d9f8aad927ac799e8b24f80fc80d89b2eb7131">arm_compute::MagnitudeType::L2NORM</a></div><div class="ttdoc">L2 normalization type. </div></div>
<div class="ttc" id="_magnitude_8h_xhtml"><div class="ttname"><a href="_magnitude_8h.xhtml">Magnitude.h</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">arm_compute::test::SimpleTensor</a></div><div class="ttdoc">Simple tensor object that stores elements in a consecutive chunk of memory. </div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00059">SimpleTensor.h:59</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_1_1reference_xhtml_a83372886e5f41e1cd3631035d638c00b"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#a83372886e5f41e1cd3631035d638c00b">arm_compute::test::validation::reference::scale</a></div><div class="ttdeci">SimpleTensor&lt; T &gt; scale(const SimpleTensor&lt; T &gt; &amp;in, float scale_x, float scale_y, InterpolationPolicy policy, BorderMode border_mode, T constant_border_value, SamplingPolicy sampling_policy, bool ceil_policy_scale)</div><div class="ttdef"><b>Definition:</b> <a href="validation_2reference_2_scale_8cpp_source.xhtml#l00040">Scale.cpp:40</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ae46abc5ecac309cbece5c06cb80daaf7a5515a637eda61b978e97adaa5d7629cc"><div class="ttname"><a href="namespacearm__compute.xhtml#ae46abc5ecac309cbece5c06cb80daaf7a5515a637eda61b978e97adaa5d7629cc">arm_compute::GradientDimension::GRAD_XY</a></div><div class="ttdoc">x and y gradient dimension </div></div>
<div class="ttc" id="_h_o_g_descriptor_8h_xhtml"><div class="ttname"><a href="_h_o_g_descriptor_8h.xhtml">HOGDescriptor.h</a></div></div>
<div class="ttc" id="_derivative_8h_xhtml"><div class="ttname"><a href="_derivative_8h.xhtml">Derivative.h</a></div></div>
<div class="ttc" id="classarm__compute_1_1_size2_d_xhtml_a02bed8590a9ddf520e58a060059518ec"><div class="ttname"><a href="classarm__compute_1_1_size2_d.xhtml#a02bed8590a9ddf520e58a060059518ec">arm_compute::Size2D::width</a></div><div class="ttdeci">size_t width</div><div class="ttdoc">Width of the image region or rectangle. </div><div class="ttdef"><b>Definition:</b> <a href="_size2_d_8h_source.xhtml#l00092">Size2D.h:92</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_a673665b4587a2956fcbad5f0e9ba89d3"><div class="ttname"><a href="namespacearm__compute.xhtml#a673665b4587a2956fcbad5f0e9ba89d3">arm_compute::HOGNormType</a></div><div class="ttdeci">HOGNormType</div><div class="ttdoc">Normalization type for Histogram of Oriented Gradients (HOG) </div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00530">Types.h:530</a></div></div>
<div class="ttc" id="classarm__compute_1_1_size2_d_xhtml"><div class="ttname"><a href="classarm__compute_1_1_size2_d.xhtml">arm_compute::Size2D</a></div><div class="ttdoc">Class for specifying the size of an image or rectangle. </div><div class="ttdef"><b>Definition:</b> <a href="_size2_d_8h_source.xhtml#l00034">Size2D.h:34</a></div></div>
<div class="ttc" id="classarm__compute_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarm__compute_1_1_tensor_info.xhtml">arm_compute::TensorInfo</a></div><div class="ttdoc">Store the tensor&amp;#39;s metadata. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_info_8h_source.xhtml#l00045">TensorInfo.h:45</a></div></div>
<div class="ttc" id="classarm__compute_1_1_h_o_g_info_xhtml_ae3664b841732a09d7749953ca5b81373"><div class="ttname"><a href="classarm__compute_1_1_h_o_g_info.xhtml#ae3664b841732a09d7749953ca5b81373">arm_compute::HOGInfo::num_bins</a></div><div class="ttdeci">size_t num_bins() const </div><div class="ttdoc">The number of histogram bins for each cell. </div></div>
<div class="ttc" id="classarm__compute_1_1_h_o_g_info_xhtml_a13a9a6f5cfa21b3ab15b1e4315311aeb"><div class="ttname"><a href="classarm__compute_1_1_h_o_g_info.xhtml#a13a9a6f5cfa21b3ab15b1e4315311aeb">arm_compute::HOGInfo::block_size</a></div><div class="ttdeci">const Size2D &amp; block_size() const </div><div class="ttdoc">The block size in pixels. </div></div>
<div class="ttc" id="classarm__compute_1_1_size2_d_xhtml_ab220a7dd0ff5c86b4ba8acdf75af3252"><div class="ttname"><a href="classarm__compute_1_1_size2_d.xhtml#ab220a7dd0ff5c86b4ba8acdf75af3252">arm_compute::Size2D::area</a></div><div class="ttdeci">size_t area() const </div><div class="ttdoc">The area of the image or rectangle calculated as (width * height) </div><div class="ttdef"><b>Definition:</b> <a href="_size2_d_8h_source.xhtml#l00053">Size2D.h:53</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_1_1reference_xhtml_a6aa278cb3dd1777e7338c5e573c55550"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#a6aa278cb3dd1777e7338c5e573c55550">arm_compute::test::validation::reference::magnitude</a></div><div class="ttdeci">SimpleTensor&lt; T &gt; magnitude(const SimpleTensor&lt; T &gt; &amp;gx, const SimpleTensor&lt; T &gt; &amp;gy, MagnitudeType magnitude_type)</div><div class="ttdef"><b>Definition:</b> <a href="validation_2reference_2_magnitude_8cpp_source.xhtml#l00035">Magnitude.cpp:35</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a6743f0a130e8311e6f5b1a23df102472"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a6743f0a130e8311e6f5b1a23df102472">arm_compute::test::validation::src</a></div><div class="ttdeci">convolution configure &amp; src</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_convolution_8cpp_source.xhtml#l00147">Convolution.cpp:147</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_1_1reference_xhtml_ae01f1c200a32d41a056d513760981326"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#ae01f1c200a32d41a056d513760981326">arm_compute::test::validation::reference::hog_block_normalization</a></div><div class="ttdeci">void hog_block_normalization(SimpleTensor&lt; T &gt; &amp;desc, const SimpleTensor&lt; T &gt; &amp;hog_space, const HOGInfo &amp;hog_info)</div><div class="ttdef"><b>Definition:</b> <a href="validation_2reference_2_h_o_g_descriptor_8cpp_source.xhtml#l00174">HOGDescriptor.cpp:174</a></div></div>
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